The present invention relates generally to the storage and retrieval of medical information using a computer, and more particularly to a method of analyzing a comprehensive collection of medical patient data through the use of a medical database.
In many fields of medicine, e.g. neurology, cardiology, surgery, etc., it is often useful to retain patient data in a manner that is readily available for future evaluation. Storage and manipulation of medical data are especially desirable in accessing the facts for analysis, where medical practitioners perform clinical research and quality assurance of medical care.
Traditionally, patient information is stored on hard copy files and in large electronic storage archives, e.g. hospital information systems (HIS). Such storage mediums usually only contain data from a local healthcare site and not data from remote locations. These storage means are generally adequate for retrieval of information about individual patients.
However, it is also very useful to view multiple patient data in aggregate and to compare the data, such as with the assistance of a computer database. The access and review of medical data from cases having similarities to a current case may assist in the treatment of a patient. In other applications, transformation of raw clinical data into comprehensive information provides invaluable knowledge. Computer databases may assist in storing a cohort description of data to describe a group of patients that have a common attribute. Furthermore, data patterns may be analyzed in terms of trends or associations with the use of databases. By predictive modeling, data may be used to derive knowledge of relationships and provide quality assurance of a medical entity.
Quality assurance of medical treatment includes the assessment of many factors. The level of care furnished by medical providers may be determined by the degree to which health services increase the likelihood of a desired health outcome. In general, level of care involves assessment of risk factors compared to outcome. The structure of care may also be evaluated by reference to the facility, the equipment, the services, the personnel available for care, and the qualifications of the involved health professionals. The process of care is another factor that includes the services provided and the process by which patients are moved through the system. Accessibility may be determined by the degree of ease or difficulty that individuals have in obtaining healthcare. Furthermore, appropriateness of care is the extent to which care complies with accepted or is within standard practice of the community, including costs and charges. Is there supposed to be a journal name here? 1995;60:1514-21.
The type of information that is availability for use in analysis is critical for conducting fair assessments of care. Databases should include precise definitions of all the terms used in order to avoid inaccurate reporting. Comparisons across patients and healthcare institutions require adequate description of those patients studied in order to group those having comparable probabilities in response to other treatment, i.e. must discriminate between groups of patients. The data should also be useful in plotting the course of illness. Rules for ranking data should be objective, reproducible, meaningful and reliable.
Furthermore, a comprehensive selection of data that is appropriate for quality assurance and research must be stored. Excluded information may result in skewed conclusions. For example, where an audit is performed on outcomes of one treatment regimen, e.g. surgery, descriptions of clinical presentations and other treatments should be considered. Otherwise, medical practitioners who refuse particular treatments for advanced cases produce more favorable outcome data for the remaining treated patients. If no treatment is performed, this information should be recorded and taken into consideration in the assessment of outcomes and quality assurance. In addition, if some risk factors are excluded from the data, a higher observed-to-expected ratio results. Gaming may also occur, where risk factors are over reported by a healthcare facility. Well planned databases allow for cohort studies for determining factors associated with good or bad outcomes.
Currently, databases store limited patient information, often in the form of codes that follow the International Classification of Diseases (ICD-10). In general, the ICD-10 standard indicates the pathology of medical conditions. However, ICD-10 codes are insufficient to accurately conduct most patient data analyses.
The selection of ICD-10 codes to represent the diagnosis of a patient""s condition may be biased by various factors, such as the specialty of an admitting physician. For example, in coding for cerebrovascular disease, where the admitting physician is a surgeon, the discharge coding may reflect the condition of specific arteries, whereas if the physician is a neurologist or internist, the code assignment may be more likely to reflect the symptomatic status of the patient. See Inaccuracy of the International Classification of Diseases in Identifying the Diagnosis of Ischemic Cerebrovascular Disease, Neurology, 1997, Sep. 49:3, 660-4. Moreover, for some conditions, the coding system does not have sufficient data options to accurately reflect the condition. See Limits of ICD-9-CM Code Usefulness in Epidemiological Studies of Contact and Other Types of Dermatitis, Am J Contact Dermat., 1998, Sep. 9:3, 176-8. As a result, frequently such codes have proven to be inaccurate representations of patients"" conditions.
Furthermore, ICD-10 codes depict only a small portion of the medical information that is useful for specific analytical applications. The ICD-10 codes do not allow for cross comparison between branches of data options and only has limited descriptive information. In order to extract information for research and quality assurance, more coded information is needed, such as clinical symptoms and signs, pathology, anatomy, treatment, outcome and data options thereof.
Moreover, it is advantageous for data storage and manipulation mediums to be flexible, so as to accommodate a variety of information/data. Medical information may take numerous forms, including text, images and video, or variations thereof, such as image overlay data, measurements, coordinates, etc. Information may also be in the form of time-dependent data including sound, such as audio dictation, and waveform data. The data may also be static representations of time-dependent forms, such as curves.
According to most current practices, multimedia data are generally archived by healthcare facilities by a patient identification number. Hence, there is no mechanism to readily access multimedia data that relate to particular patient descriptions, such as treatment, anatomy, pathology, etc. Instead, a patient list must be generated and each individual patient""s multimedia records retrieved for review. This process is tedious and inefficient for analyses across large numbers of patients and complex investigations.
Thus, in light of the shortcomings of the various currently available systems, there is still a need for systems that enable simple access to many types of data and from several healthcare sites. In particular, there is a desire for a database that allows for storage and manipulation of a highly descriptive body of medical data that is useful for accurate research and quality analysis. The system should allow for searching across multiple layers of variables. It would be further useful for the information to be available in a form for easy dissemination, such as in presentations and reports.
In one embodiment, a computer assisted method for analyzing medical patient data by storing and accessing relevant data is provided. The type of data that is stored and the relational manner in which they are stored allow for comprehensive searches. The steps in the method may comprise selecting patient data from a list of data options in at least one category. The categories are clinical presentation, pathology, anatomy, treatment and outcome, although additional categories may also exist. Often, the data options of the categories are arranged in a database within table by decreasing levels of specificity in a hierarchical tree. The patient data are stored with a unique identifier to relate all of the patient data within a data set. In another step, the user conducts a search of stored data by selecting at least one criterion for particular patient data from at least one of the categories. The particular patient data are retrieved.
At various times, the patient data are selected from a list of data options within at least two of the categories, such as treatment and outcome, at least three of the categories, at least four of the categories or all five categories. Furthermore, the list of categories may include a provider category. At least one of the criteria may be employed for particular patient data from this provider category. At still other times, at least one of the data options in at least one of the categories is related to custom prospective data provided in a custom screen table that is created by a user and stored within the database. Conveniently, one method allows for selection of patient data by pointing onto a location on a graphic representation of an anatomy.
A variety of types of analyses are possible with the database. In particular applications, the patient data that are extracted from a query search is analyzed by the database and the statistical results are optionally displayed, such as a graph form, e.g. pie chart, bar chart, etc.
In some methods, multimedia data that are related to the particular patient data by the identifier is retrieved. The multimedia data may include video, image, electronic waveform and sound data, and the like, or combinations thereof. In some cases, the multimedia data is retrieved from a storage component in the relational database. In other instances, the multimedia data is stored on a remote server that is communicatively coupled to the relational database, and retrieved therefrom. In any event, some or all of the multimedia data may be selected and conveniently transferred to a presentation applications file.
A medical patient data analysis system for use in employing the above described methods typically includes a processor; an input device in communication with the processor for receiving patient data; and a storage unit in communication with the processor. The storage unit has a relational database for storing data options within data option category tables by decreasing levels of specificity in a hierarchical tree. The data option category tables are selected from the group consisting of clinical presentation, pathology, anatomy, treatment and outcome. The database is further used for storing patient data of a data set having a unique identifier within category tables, the patient data being chosen from the data options in at least one data option category table. The processor has a means for receiving patient data from the input and storing the patient data in the storage unit; a means for receiving instructions from the input for selecting at least one criterion for particular patient data from at least one category table; and a means for retrieving the particular patient data. In one embodiment, a display that is in communication with the processor is provided.
Still other embodiments may provide a computer readable medium having stored therein a plurality of sequences of instructions, which, when executed by a processor, cause the processor to perform certain steps. Among these steps may be included the steps of receiving medical patient data of a data set from an input device. The patient data consists of a selected data option from a hierarchical tree having data options arranged in decreasing levels of specificity. Another step may be determining whether the patient data includes an identifier. If no identifier is present, the processor attaches a unique identifier to the patient data. The process may facilitate the patient data to be stored in a relational database within tables of categories. The categories may include clinical presentation, pathology, anatomy, treatment and outcome. Responsive to instructions received from the input device, the process may retrieve particular patient data that are associated with at least one selected criterion. The patient data may include multimedia data. Of course, other embodiments may provide only the instructions themselves or the instructions as carried in a data signal by a carrier wave.
According to still further embodiments, a server may be provided for use in analysis of medical patient data, according to the present invention. Such a server may include a network interface for acquiring patient data of a patient set from a network. The patient data is chosen from at least one data option from a hierarchical category tree having data options arranged in decreasing levels of specificity. A storage unit is also provided in the server. The storage unit is coupled to receive the patient data from the data interface and to store the patient data within table of categories selected from the group consisting of clinical presentation, pathology, anatomy, treatment and outcome. The patient data of a data set has an attached unique identifier. Further to the server is usually an assembly unit coupled to the network interface and storage unit to gather selected portions of the patient data in response to instructions from a user station. In alternative embodiments of the server, an activation unit is present for determining whether patient data were received by the user station prior to sending instructions for selected portions of patient data.
In a network system, a user station may be provided having an input device for receiving patient data. A processor in the user station has a means for receiving patient data from the input device. The patient data is at least one chosen data option from a category in a tree format as described above. The category is also selected from the group including clinical presentation, pathology, anatomy, treatment and outcome. The process also typically has a means for forming instructions by selecting at least one criterion from at least one of the categories. The user station may also have a browser for sending the instructions and the patient data into a network and receiving selected portions of patient data from the network.
One method of conducting data analysis using a public network includes assembling the patient data into packets. At least one criterion from at least one category is selected and a request is made to a server for selected medical patient data associate with the at least one criterion. The packets having the patient data are sent into the public network for receipt at the server. Thereafter, the selected patient data is received from the server. In one variation of method, the patient data are encrypted prior to sending the packets into the network.
The benefits of the medical patient data analysis system are direct in that a comprehensive assortment of medical data may be stored for easy access and manipulated for accurate research and quality analysis. The categories provide detailed patient descriptions from which data may be retrieved. The invention also provides a convenient way for multimedia data to be retrieved. Moreover, the relationship of the data options to each other in a hierarchical tree allows for further sophisticated searches to be conducted. Thus, clinical research and quality assurance of healthcare providers is greatly facilitated.
Other features and advantages of these and other embodiments are discussed in detail below.